Department of Data Science


Coordinator, Data Science


Welcome Remarks from the Coordinator of the Department
"Unleashing the Power of Data"

It is a privilege to welcome you to the Department of Data Science. You are embarking on an exciting and rewarding academic journey that will equip you with the skills to drive innovation and solve complex problems using data.

In today’s data-driven world, the demand for skilled data scientists has never been higher. You are joining a field at the forefront of technological advancement, with opportunities to work in a wide range of industries, from healthcare and finance to marketing and e-commerce.

Our department is committed to providing you with a strong foundation in mathematics, statistics, computer science, and domain-specific knowledge. You will learn how to collect, clean, analyze, and interpret data to extract valuable insights. We also emphasize critical thinking, problem-solving, and communication skills, which are essential for success in this field.

Beyond the classroom, we encourage you to explore your interests through research projects, internships, and extracurricular activities. Our department offers a supportive environment where you can collaborate with faculty and peers, and develop your professional network.

I am confident that your time at our department will be both challenging and fulfilling. I encourage you to embrace the opportunities, ask questions, and never stop learning.

Welcome once again, and I wish you all the best in your academic journey.

Thank you.



Philosophy

The philosophy of the bachelor’s degree in Data Science at Summit University, Offa (SUN, Offa), is to produce graduates with capacities and skills in Data Science and grounded in the unwavering commitment to cultivate a cadre of highly skilled professionals who stand as guardians of the digital realm.

Our primary goal is to equip graduates with unparalleled expertise, enabling them to navigate the intricate web of Data Science challenges and emerge as stewards of secure and resilient digital ecosystems.


Activity

The Data Science program in COICT at Summit University, Offa (SUN, Offa), is a dynamic field with endless possibilities for exploration. As an undergraduate, engaging in hands-on projects is crucial for building a strong foundation and developing practical skills.

The COICT of Summit University, Offa (SUN, Offa) has mapped out some activities to kick start undergraduates' data science journey with:

Foundational Activities

  • Learn Programming Languages: Master Python and R, the industry standards for data manipulation, analysis, and visualization.
  • Grasp Statistical Concepts: Understand probability, hypothesis testing, regression, and other statistical methods.
  • Explore Data Visualization: Learn to create compelling visualizations using libraries like Matplotlib, Seaborn, and Plotly.
  • Online Courses and Tutorials: Take advantage of platforms like Coursera, edX, DataCamp, and Kaggle for structured learning.
  • Data Cleaning and Preprocessing: Practice handling messy real-world data, including missing values, outliers, and inconsistencies.

Project-Based Learning

  • Kaggle Competitions: Participate in data science challenges to solve real-world problems and learn from others.
  • Personal Projects: Explore your interests by working on projects related to your hobbies or passions.
  • Open-Source Contributions: Contribute to open-source data science projects to collaborate with others and give back to the community.
  • Data Science Clubs or Organizations: Join campus clubs to network with peers and work on group projects.
  • Internships and Co-ops: Gain practical experience by working in industry and applying your skills to real-world problems.

Specific Project Ideas

  • Predictive Modeling: Build models to predict customer churn, stock prices, or disease outbreaks.
  • Natural Language Processing (NLP): Analyze text data for sentiment analysis, topic modeling, or text classification.
  • Image and Video Analysis: Explore computer vision techniques for object detection, image recognition, or video analysis.
  • Web Scraping: Extract data from websites and create valuable datasets for analysis.
  • Data Storytelling: Communicate insights effectively through visualizations and narratives.

Research Activity

Undertaking research in data science at Summit University, Offa (SUN, Offa) as an undergraduate can be a rewarding experience, providing valuable insights and skill development. Here are some potential research activities:

Potential Research Areas

  • Predictive Modeling:
    • Developing models to forecast stock prices, weather patterns, or disease outbreaks.
    • Exploring different machine learning algorithms and their performance.
  • Natural Language Processing (NLP):
    • Analyzing sentiment in social media data.
    • Developing text summarization or classification models.
    • Investigating language models and their applications.
  • Image and Video Analysis:
    • Object detection and recognition in images.
    • Video analysis for action recognition or anomaly detection.
    • Image generation or manipulation using generative models.
  • Data Mining and Knowledge Discovery:
    • Discovering patterns and trends in large datasets.
    • Developing association rule mining algorithms.
    • Applying data mining techniques to specific domains (e.g., healthcare, finance).
  • Big Data Analytics:
    • Exploring big data technologies (Hadoop, Spark).
    • Developing scalable data processing pipelines.
    • Analyzing large-scale datasets for insights.

Research Methodology

  • Literature Review: Understand the existing research in your chosen area.
  • Data Collection: Gather relevant data from various sources (e.g., public datasets, APIs, surveys).
  • Data Preprocessing: Clean and prepare data for analysis.
  • Exploratory Data Analysis (EDA): Understand the data through visualization and summary statistics.
  • Model Building and Evaluation: Develop and evaluate data science models.
  • Result Interpretation and Communication: Present findings clearly and effectively.

Potential Research Projects

  • Analyzing social media data to understand public opinion on a specific topic.
  • Developing a predictive model for customer churn in a particular industry.
  • Investigating the impact of climate change on agricultural yields.
  • Building a recommendation system for products or services.
  • Analyzing traffic patterns to optimize transportation systems.
  • Exploring the use of machine learning for fraud detection.

Admission Requirement

There are three modes of admission into the Bachelor’s Degree Data Science Programme at Summit University, Offa. These are the UTME mode, Direct Entry (DE) mode, and Inter University Transfer. Admission requirements for the two modes are subsequently presented herewith.

Compliance with UTME Admission Requirements

  • Credit in five O' Level subjects at General Certification of Education (GCE), Senior Secondary Certificate Education (SSCE), or an equivalent that must include Mathematics, Physics, Chemistry, English Language, and any other science subject such as Biology, Agricultural Science, or Further Mathematics. The five Credits must be obtained at not more than two sittings.
  • For the four-year degree programme, in addition to acceptable passes in the Unified Tertiary Matriculation Examination (UTME), the minimum admission requirement is credit level passes in Senior School Certificate (SSC) in at least five subjects, which must include English Language, Mathematics, Physics, Chemistry, and other acceptable science subjects at not more than two sittings.
  • Candidates must pass the University Tertiary Matriculation Examination in English Language, Mathematics, Chemistry, and Physics.

Direct Entry Admission Requirements

  • Holders of Upper Credit Level in National Diploma in Computer Science, Data Science, Cyber Security, and other relevant programmes may qualify for admission at 200 Level in addition to five (5) Senior School Certificate (SSC) credit passes, which must include English Language, Mathematics, Physics, and Chemistry.
  • Candidates with at least two passes in relevant subjects (Mathematics, Physics, and Chemistry) at the GCE Advanced Level, IJMB, or JUPEB may be considered for admission into 200 Level.
  • Holders of HND with at least Upper Credit or Lower Credit in Computer Science, Data Science, or Computer Engineering, in addition to five O’Level credit passes, which must include English Language, Mathematics, Physics, and Chemistry, may qualify for admission at 200 Level.
  • Direct Entry candidates are required to pass the O' Level grades stipulated in the UTME requirements. Direct Entry students must also take and pass the General Studies courses offered at 100 and 200 Levels.

Inter University Transfer

All candidates seeking transfer (Inter University) must have spent a minimum of one academic session in the programme of first admission with full sessional results attached to the application for transfer.

All Inter University candidates seeking transfers to the Department of Mechatronics Engineering must:

  • Be studying a related programme in their current university.
  • Have passed all courses registered in their current university before seeking the transfer.
  • Have a minimum CGPA of 2.00 on a scale of 5.00.
  • Transfer cases can only be entertained up to and not beyond 200 Level.

Note:

  • Admission is purely based on available vacancies in the Department.
  • The number of candidates applying for admission.

Duration of the Programme

The Data Science Programme is designed to last for a minimum of four (4) years and a maximum of 6 years for UTME candidates, or a minimum of three (3) years for DE (200 Level) candidates and a maximum of 4.5 years.